Implementations of the claimed invention generally may relate to the field of noise detection, and in particular to noise detection and estimation in images and/or video.
In the area of image/video applications, picture noise is an undesirable picture viewing appearance that may be caused by any of the imperfect processes of video capturing, transmission, and/or storage. Reducing the visual artifacts of picture noise is an important pursuit in the fields of noise filtering. In general, it is known that noise filtering usually blurs the high-detailed content in addition to removing noise. For this reason, it may be desirable not to apply the noise filtering unless it is determined with a reasonable degree of certainty that the picture noise is visually apparent in the picture. Thus, a noise detection device is typically needed for the proper, selective application of noise filtering.
A noise detection device may produce two pieces of information: the occurrence of the noise and the strength of the noise level. A noise detection device may use a single value, for example, it has a non-zero value when noise is present, and a zero or null value when noise is not present. The magnitude of the non-zero value may indicate the strength of the detected noise.
Several approaches have been proposed to detect noise in images/video. One such proposed approach may use the non-active video areas (blanking lines) for measuring the amount of noise, with the assumption that the signal perturbation in these areas comes from the noise only. One issue with this approach is that one cannot be sure if the blanking line may be inserted or cleaned somewhere in an early stage of the video process. Thus, what is assumed to be noise within the blanking line may not in fact be, or in any event may not correspond to the noise within the image or video.
Another such proposed approach may use motion detection based on the concept that the area with the minimal motion detection output contains no motion, but a temporal difference that is only due to noise. An issue with such motion detection approaches may be that there is no reliable motion detection information for a period of scene change. Also, the computation and memory complexities involved in the proposed motion detection approach are relatively expensive.
Such proposed approaches to noise detection in images/video may not accurately reflect actual noise in the picture(s), and/or may perform poorly during scene changes. Further, some proposed approaches may not be cost effective in terms of needed circuitry and/or the associated temporal latency.